Gotta Plot ’Em All!

Research Question

This visualization attempts to find our how Pokemon’s strength changed throughout generations (1-6) and if not-legendary Pokemon can defeat legendary, and what are they?

Pokemon Information

generations:

I Generation - (1996-1999) New Pokemon - 151

II Generation - (1999-2001) New Pokemon - 100

III Generation - (2002-2005) New Pokemon - 135

IV Generation - (2006-2010) New Pokemon - 107

V Generation - (2010-2013) New Pokemon - 156

VI Generation - (2013-2016) New Pokemon - 72

legendary:

Legendary Pokemon are incredibly rare and often very powerful Pokemon, generally featured prominently in the legends and myths of the Pokemon world.

information source: https://bulbapedia.bulbagarden.net/wiki/Legendary_Pok%C3%A9mon and https://bulbapedia.bulbagarden.net/wiki/Generation .

Data Origins

The data consists of 721 Pokemon and specific for each of them attributes such as HP, Attack, Type.1 etc.

Pokemon data that was used for this project and can be found at: pokemon data

data <- read.csv("data/pokemon_data.csv") #load data

#there are 13 variables which are:
names(data)
##  [1] "X."         "Name"       "Type.1"     "Type.2"     "Total"     
##  [6] "HP"         "Attack"     "Defense"    "Sp..Atk"    "Sp..Def"   
## [11] "Speed"      "Generation" "Legendary"

Data Preparation

#tidying and removing all except variables we need
df <- data %>% tibble::as_tibble() %>% 
   distinct(X., .keep_all = TRUE) %>% 
  select(Name, Type.1, Total, Generation, Legendary) %>%
   dplyr::rename(type = Type.1,
         name = Name,
         total = Total,
         generation = Generation,
         legendary = Legendary) %>%
  arrange(type) %>%
  print() 
## # A tibble: 721 x 5
##    name       type  total generation legendary
##    <chr>      <chr> <int>      <int> <chr>    
##  1 Caterpie   Bug     195          1 False    
##  2 Metapod    Bug     205          1 False    
##  3 Butterfree Bug     395          1 False    
##  4 Weedle     Bug     195          1 False    
##  5 Kakuna     Bug     205          1 False    
##  6 Beedrill   Bug     395          1 False    
##  7 Paras      Bug     285          1 False    
##  8 Parasect   Bug     405          1 False    
##  9 Venonat    Bug     305          1 False    
## 10 Venomoth   Bug     450          1 False    
## # ... with 711 more rows
#tidying, changing type
df$legendary[df$legendary=="True"] <- "Legendary" 
df$legendary[df$legendary=="False"] <- "Not Legendary"

head(df,10)
## # A tibble: 10 x 5
##    name       type  total generation legendary    
##    <chr>      <chr> <int>      <int> <chr>        
##  1 Caterpie   Bug     195          1 Not Legendary
##  2 Metapod    Bug     205          1 Not Legendary
##  3 Butterfree Bug     395          1 Not Legendary
##  4 Weedle     Bug     195          1 Not Legendary
##  5 Kakuna     Bug     205          1 Not Legendary
##  6 Beedrill   Bug     395          1 Not Legendary
##  7 Paras      Bug     285          1 Not Legendary
##  8 Parasect   Bug     405          1 Not Legendary
##  9 Venonat    Bug     305          1 Not Legendary
## 10 Venomoth   Bug     450          1 Not Legendary

Visualisation 1: Rainbow Pokemon - All

g1 <- df %>%
  mutate(text=paste("Name: ",(df$name), "\nType: ",(df$type), "\nTotal: ", (df$total), sep="")) %>% 
  ggplot(df,mapping = aes(x = total, y=type, col=type, text=text)) +
  geom_point(position = "jitter")+
  labs( x="Total strength",
        y= NULL,
        title="Types of Pokemon")+
  theme_minimal()+ 
  theme(axis.text.y=element_blank(),
        plot.title = element_text(size=20))+ 
  guides(col=guide_legend("Types of Pokemon"))

p1 <- ggplotly(g1, tooltip="text") 
p1
#save output
htmlwidgets::saveWidget(p1, file="graphs/rainbow_pokemon.html")

Visualisation 2: Legendary Pokemon

names(wes_palettes)
##  [1] "BottleRocket1"  "BottleRocket2"  "Rushmore1"      "Rushmore"      
##  [5] "Royal1"         "Royal2"         "Zissou1"        "Darjeeling1"   
##  [9] "Darjeeling2"    "Chevalier1"     "FantasticFox1"  "Moonrise1"     
## [13] "Moonrise2"      "Moonrise3"      "Cavalcanti1"    "GrandBudapest1"
## [17] "GrandBudapest2" "IsleofDogs1"    "IsleofDogs2"
g2 <- df %>%
mutate(text=paste("Name: ",(df$name), "\nType: ",(df$type), "\nTotal: ", 
                  (df$total), "\nGen: ", (df$generation), "\n", 
                  (df$legendary),sep="")) %>%
ggplot(df,mapping = aes(x = generation, y=total, col=legendary, text=text)) +
  geom_point(position = "jitter")+
  labs( x=NULL,
        y= "Total strength",
        title="Legendary Pokemon")+
  theme_minimal()+
  theme(axis.text.x=element_blank(),
        axis.title.x = element_blank(),
        plot.title = element_text(size=20),
        panel.grid.major.x = element_blank())+
  guides(col=guide_legend("Types of Pokemon"))+
  scale_colour_manual(values=wes_palette("Moonrise3"))

p2 <- ggplotly(g2, tooltip="text") 
p2
#save output
htmlwidgets::saveWidget(p2, file="graphs/legendary_pokemon.html")

Visualisation 3 - Interactive Pokemon Types

g3 <- df %>%
  mutate(text=paste("Name: ",(df$name), "\nType: ",(df$type), "\nTotal: ", 
                    (df$total), "\nGen: ", (df$generation), "\n", 
                    (df$legendary),sep="")) %>%
  ggplot(df,mapping = aes(x = generation, y=total, col=type, text=text)) +
  geom_point(position = "jitter")+
  labs( x=NULL,
        y= "Total strength",
        title="All Pokemon")+
  theme_minimal()+
  theme(axis.text.x=element_blank(),
          plot.title = element_text(size=20),
          panel.grid.major.y = element_line("#e6f2ff"),
          panel.grid.major.x = element_blank(), 
          axis.line = element_line(colour = "#003166"))+
  guides(col=guide_legend("Types of Pokemon"))+
  scale_color_manual(values = c("Bug"="tan4","Dark"="black","Dragon"="chartreuse4","Electric"="darkgoldenrod1","Fairy"="hotpink","Fighting"="darksalmon","Fire"="firebrick1","Flying"="lightskyblue","Ghost"="darkblue","Grass"="yellowgreen", "Ground"="peru","Ice"="cadetblue1","Normal"="pink","Poison"="maroon","Psychic"="darkviolet","Rock"="wheat3","Steel"="gray","Water"="steelblue1"))

p3 <- ggplotly(g3, tooltip="text") 
p3
#save output
htmlwidgets::saveWidget(p3, file="graphs/all_types_interactive.html")

Visualisation 4: Animated Pokmon All

g4 <- ggplot(df,mapping = aes(x = generation, y=total, col=type)) +
  geom_point(position = "jitter", size=2)+
  labs(title="Now showing {closest_state} Pokemon",
       subtitle = 'Frame {frame} of {nframes}',
       x=NULL,
       y= "Total strength")+
  theme_minimal()+
  theme(axis.text.x=element_blank(),
        axis.title.y = element_text(size=15),
        plot.title = element_text(size=20),
        panel.grid.major.y = element_line("#e6f2ff"),
        axis.line = element_line(colour = "#003166"),
        legend.position = "none")+ #removes legend
  transition_states(type,
                    transition_length = 20,
                    state_length = 10,
                    wrap = FALSE)+
  enter_fade()+ 
  exit_fade()+
  scale_color_manual(values = c("Bug"="tan4","Dark"="black","Dragon"="chartreuse4","Electric"="darkgoldenrod1","Fairy"="hotpink","Fighting"="darksalmon","Fire"="firebrick1","Flying"="lightskyblue","Ghost"="darkblue","Grass"="yellowgreen", "Ground"="peru","Ice"="cadetblue1","Normal"="pink","Poison"="maroon","Psychic"="darkviolet","Rock"="wheat3","Steel"="gray","Water"="steelblue1"))

animate(g4 + ease_aes(), width=600,height=600) 

#save output
anim_save(file="graphs/all_types_animated.gif")

Summary Discussion

Caveat #1: Type.2 of Popkemon were not look at, which might be interesting to do so in the future.

Caveat #2: 2 new generations (VII[2016-2019] and VIII [2019-2022]) were not included in the data and there are 177 new Pokemon.

Caveat #3: Comparison of each attributes of Total Score such as HP and Attack might be worth looking at